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Identification of behavioural model input data sets for WWTP uncertainty analysis
IVL Swedish Environmental Research Institute.
2020 (English)In: Water Science and Technology, ISSN 0273-1223, E-ISSN 1996-9732, Vol. 81, no 8, p. 1558-1568Article in journal (Refereed) Published
Abstract [en]

Uncertainty analysis is important for wastewater treatment plant (WWTP) model applications. An important aspect of uncertainty analysis is the identification and proper quantification of sources of uncertainty. In this contribution, a methodology to identify an ensemble of behavioural model representations (combinations of input data, model structure and parameter values) is presented and evaluated. The outcome is a multivariate conditional distribution of input data that is used for generating samples of likely inputs (such as Monte Carlo input samples) to perform WWTP model uncertainty analysis. This article presents an approach to verify uncertainty distributions of input data (otherwise often assumed) by using historical observations and actual plant data.

Place, publisher, year, edition, pages
2020. Vol. 81, no 8, p. 1558-1568
Identifiers
URN: urn:nbn:se:ivl:diva-3272OAI: oai:DiVA.org:ivl-3272DiVA, id: diva2:1554858
Note
A-rapport, A2529Available from: 2021-05-17 Created: 2021-05-17

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